2026-10-14T21:58:15Z https://www.scidb.cn/oai

10.57760/sciencedb.40300 2026-06-24T19:17:02Z

2026-06-24 change detection dataset doi:10.57760/sciencedb.40300 en WHU-CD dataset: With a spatial resolution of 0.2 meters, this dataset consists of a pair of large-format (32,507 × 15,354 pixels) dual-temporal aerial images. It primarily covers reconstruction areas in the years following an earthquake, focusing on changes in buildings. In the experiments, the original images were cropped into 256 × 256 pixel patches, and the dataset was split into training, validation, and test sets in an 8:1:1 ratio.  LEVIR-CD dataset: Sourced from Google Earth, with a spatial resolution of 0.5 meters and an original image size of 1024×1024 pixels. This dataset exhibits significant land-use changes, particularly including various types of building changes.In the experiment, non-overlapping cropping was used to generate 256×256 image patches, resulting in a total of 7,120 training patches, 1,024 validation patches, and 2,048 test patches.  CLCD Dataset: Composed of 2017 and 2019 Gaofen-2 satellite images, it contains 600 pairs of 512×512 dual-temporal samples with a spatial resolution of 0.5–2 meters.The changes in land cover are primarily related to cropland, while also covering various land features such as buildings, roads, lakes, and bare ground. For the experiments, the images were cropped to 256×256, with 320 pairs used for training, 120 pairs for validation, and 120 pairs for testing. change detection; WHU-CD dataset; LEVIR-CD dataset; CLCD Dataset meiyong PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank